1. Field of the Invention
The present invention relates to a system and a method of monitoring a queue, and more particularly, to a system and a method of monitoring a queue that allow for exactly recognizing objects in a queue and exactly monitoring the situation of the queue by tracking the recognized objects, using depth detection device such as a TOF camera.
2. Description of the Related Art
Recently, with development of various object tracking algorisms for tracking objects in an image taken by cameras and development of the capacity of cameras, systems for monitoring objects using those algorisms and devices have been considerably developed.
Such systems for monitoring objects are applied to various fields such as measuring traffic, counting visitors, or monitoring a queue, in addition to a system for monitoring invaders or abnormal situations.
Existing systems for monitoring objects acquires an image by photographing objects in an actual 3D space, using a camera, in which the objects in the image are different in size in accordance with the distances from the camera, and even the same objects may be different in size, so it is required to calibrate the camera in order to exactly recognize desired objects in the image.
Accordingly, those systems for monitoring object receive initial parameters (height, angle, FOV, and the like) of a camera, map an actual 3D photographing space to an image taken by the camera, and perform calibration such that objects in the 3D space exactly correspond to the object in the image.
However, according to the calibration, it is required to set the size values of every objects and the depth value of the space to correspond to the positions of the objects in a 3D space, so the process of mapping the 3D space to the actual image is very complicated. Further, even if they are the same objects, it is required to specifically set the relationships of the objects in the 3D space and the object in the 2D image in consideration of the initial parameters of the camera and the different in size according to the positions of the objects in the 3D space, so those systems are considerably complicated. Further, if a space is complicated, it is further difficult to set the relationships between the setting values obtained by mapping a 3D space to an image and other setting values, so setting is very difficult.
Further, according to existing systems for monitoring objects that monitors a queue by mapping a 3D space to an image, when objects frequently change in size due to continuous movement of a queue in the process of tracking people in the queue as objects, the systems frequently fail to track the recognized objects, so reliability and exactness of the systems significantly decrease.